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A machine learning approach to predict progression on active surveillance for prostate cancer

Madhur Nayan, Keyan Salari, Anthony Bozzo, Wolfgang Ganglberger, Gordan Lu, Filipe L.F. Carvalho, Andrew Gusev, Adam Schneider, Brandon Westover, Adam S. Feldman

2021Urologic Oncology Seminars and Original Investigations29 citationsDOIOpen Access PDF

Topics & Concepts

Random forestProstate cancerMachine learningArtificial intelligenceLogistic regressionSupport vector machineCohortArtificial neural networkMedicineTest setOncologyCancerComputer scienceInternal medicineProstate Cancer Diagnosis and TreatmentAI in cancer detectionStatistical Methods in Epidemiology
A machine learning approach to predict progression on active surveillance for prostate cancer | Litcius